ABSTRACT The Rough Set (RS) theory can be considered as a tool to reduce the input
dimensionality and to deal with vagueness and uncertainty in datasets. Over the years, there …

This paper presents a distributed genetic algorithm for the discovery of classification rules.
Population is contained in the form of interconnected demes. The local selection and …

Decision tree models have earned a special status in predictive modeling since these are
considered comprehensible for human analysis and insight. Classification and Regression …

The voluminous amount of data stored in databases contains hidden knowledge which
could be valuable to improve decision making process of any organization. As it is not …

Automated discovery of rules with exceptions and hierarchical structures is an important
problem in data mining. A knowledge structure based on Censored Production Rules with …

The voluminous amount of data stored in databases contains hidden knowledge which
could be valuable to improve decision making process of any organization. As it is not …

Abstract Conventional Fuzzy Classification Rules (FCRs) are most often discovered in the
form of flat 'If-Then'rules. These flat rules increase the size of Fuzzy Rule Based Systems …

Most of the classification algorithms discover flat Fuzzy Classification Rules (FCRs) in 'If-
Then'form. The knowledge discovered in the form of FCRs allows us to deal with vague …

The accurate representation of sets in crisp set is known as rough set. The knowledge is
obtained by considering every data as objects with its discourse to extract associated …

Automated discovery of decision rules is a research area of significant importance as the
discovered rules improve the decision making process in various real world situations …